Optimizing the lattice design of a diffraction-limited storage ring with a rational combination of particle swarm and genetic algorithms

作     者：焦毅 徐刚 

作者机构：Key Laboratory of Particle Acceleration Physics and Technology Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China 

出 版 物：《Chinese Physics C》 (中国物理C（英文版）)

年 卷 期：2017年第41卷第2期

页      面：166-176页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 082701[工学-核能科学与工程] 0827[工学-核科学与技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by NSFC(11475202,11405187) Youth Innovation Promotion Association CAS(2015009) 

主　　题：diffraction-limited storage ring High Energy Photon Source multi-objective particle swarm optimization multi-objective genetic algorithm lattice design 

摘      要：In the lattice design of a diffraction-limited storage ring（DLSR） consisting of compact multi-bend achromats（MBAs）, it is challenging to simultaneously achieve an ultralow emittance and a satisfactory nonlinear performance, due to extremely large nonlinearities and limited tuning ranges of the element parameters. Nevertheless, in this paper we show that the potential of a DLSR design can be explored with a successive and iterative implementation of the multi-objective particle swarm optimization（MOPSO） and multi-objective genetic algorithm（MOGA）. For the High Energy Photon Source, a planned kilometer-scale DLSR, optimizations indicate that it is feasible to attain a natural emittance of about 50 pm·rad, and simultaneously realize a sufficient ring acceptance for on-axis longitudinal injection, by using a hybrid MBA lattice. In particular, this study demonstrates that a rational combination of the MOPSO and MOGA is more effective than either of them alone, in approaching the true global optima of an explorative multi-objective problem with many optimizing variables and local optima.